Sensing in tires for rolling resistance

ABSTRACT

Described herein are systems and methods for determination of rolling resistance from a sensor or sensors in a tire or tires for application in smart cars to provide feedback to interested parties, such as Departments of Transportation or tire manufacturers.

TECHNICAL FIELD

The subject matter disclosed herein is generally directed to systems andmethods for determining rolling resistance from a sensor(s) in a tire(s)for application in smart cars to provide feedback to interested parties,such as Departments of Transportation or tire manufacturers.

BACKGROUND

Rolling resistance is force or energy that resists the movement of arolling body. Decreasing rolling resistance improves overall vehicleefficiency, increases vehicle range, and decreases emissions. Accordingto the Alternative Fuels Data Center, “an estimated 5% to 15% ofpassenger car fuel consumption is used just to overcome rollingresistance.”https://www.tirebuyer.com/education/rolling-resistance-and-fuel-economy

Rolling resistance is caused by: (1) deformation in a tire as it rolls;and (2) road surface. Rolling resistance includes mechanical energylosses due to aerodynamic drag associated with rolling, friction betweenthe tire and road and between the tire and rim, and energy losses takingplace within the structure of the tire. Due to the weight of thevehicle, the bottom part of a tire flattens as it rolls, the part of thetire that flattens changes. This constant changing of shape leads toincreased resistance. Further, different pavement materials and surfacetextures lead to different rolling resistances. Smoother roads createless rolling resistance than rougher roads.

Accordingly, it is an object of the present disclosure to providesystems and methods for comparing how tires react over range and weatherconditions in order to provide rolling resistance data for the life of atire.

Citation or identification of any document in this application is not anadmission that such a document is available as prior art to the presentdisclosure.

SUMMARY

The above objectives are accomplished according to the presentdisclosure by providing in a first embodiment a system for monitoringrolling resistance across a road. The system may include a vehicle withat least one tire where the tire has at least one tire sensorincorporated into the tire, and movement of the at least one tire acrossa road surface impacts the at least one tire sensor and provides rollingresistance data for the at least one tire. Further, the at least onetire sensor may be a soft elastomeric capacitor. Further yet, the atleast one tire sensor may be on an exterior surface of the tire. Still,the at least one tire sensor may be placed within an interior structureof the at least one tire. Yet again, the system may measure energy lossthat contributes to rolling resistance of the at least one tire. Again,the system may include an integrated roadway section. Moreover, theintegrated roadway system may include a precast concreate section withat least one sensor embedded within the precast concrete. Further yet,the at least one tire sensor may measure strain in at least twodirections. Still more, deformation of the at least one tire may bemeasured to determine rolling resistance. Yet again, the at least onetire may have an airless support structure. Further again, the at leastone tire may be a 3-D printed tire. Still yet, the at least one tire maybe formed from a biodegradable polymer. Yet moreover, tread may beprinted on an outer surface of the 3-D printed tire.

In a further embodiment, a method is provided for calculating rollingresistance across a road. The method may include forming at least onetire having at least one tire sensor incorporated into a structure ofthe tire, placing the tire on a vehicle, placing at least one forcesensor within a suspension of the vehicle in communication with the atleast one tire sensor, and movement of the at least one tire across aroad surface impacts that at least one tire sensor and provides rollingresistance data for the at least one tire. Further, the at least onetire sensor may be a soft elastomeric capacitor. Still yet, the at leastone tire sensor may be placed on an exterior surface of the tire. Again,the at least one tire sensor may be placed within an interior structureof the at least one tire. Still moreover, the method may includemeasuring energy loss that contributes to rolling resistance of the atleast one tire. Yet still, the method may include driving the vehicleover an integrated roadway section. Further yet, the at least one tiremay be formed with an airless support structure.

These and other aspects, objects, features, and advantages of theexample embodiments will become apparent to those having ordinary skillin the art upon consideration of the following detailed description ofexample embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

An understanding of the features and advantages of the presentdisclosure will be obtained by reference to the following detaileddescription that sets forth illustrative embodiments, in which theprinciples of the disclosure may be utilized, and the accompanyingdrawings of which:

FIG. 1A shows an example of a Soft Elastomeric Capacitor.

FIG. 1B shows one possible method of sensor fabrication for the presentdisclosure.

FIG. 1C shows a Measurement Principle of the current disclosure (layersnot scaled).

FIG. 1D shows a laboratory setup for four SECs: (a) general setup withfour SECs installed on the bottom of the beam; (b) setup schematic—fromside; and (c) setup schematic—from under the beam.

FIG. 1E shows strain history of SEC versus RSG (step load).

FIG. 1F shows strain history of SEC versus RSG (triangular load) andactuator displacement.

FIG. 1G shows sensitivity of the SEC.

FIG. 1H shows sensitivity of the SEC under large strain levels.

FIG. 1I shows strain history for four SECs: (a) SECs; and (b) RSGs.

FIG. 1J shows deflection shapes: (a) Non-normalized; and (b) normalized.

FIG. 1K shows strain history for four SECs: (a) SECs; and (b) RSGs andactuator displacement.

FIG. 1L shows RMS error of the normalized deflection shapes with respectto the analytical solution.

FIG. 2 shows a cross section of an automobile tire.

FIG. 3 shows an illustration of tire deformation.

FIG. 4 shows a cutaway view of a section of an integrated roadwaysystem.

FIG. 5 shows an example of another embodiment of an integrated roadway.

FIG. 6 shows an example of a 3-D printed tire with biodegradable treadand an airless honeycomb structure.

FIG. 7 is an alternate embodiment of an airless tire.

The figures herein are for illustrative purposes only and are notnecessarily drawn to scale.

DETAILED DESCRIPTION OF THE EXAMPLE EMBODIMENTS

Before the present disclosure is described in greater detail, it is tobe understood that this disclosure is not limited to particularembodiments described, and as such may, of course, vary. It is also tobe understood that the terminology used herein is for the purpose ofdescribing particular embodiments only, and is not intended to belimiting.

Unless specifically stated, terms and phrases used in this document, andvariations thereof, unless otherwise expressly stated, should beconstrued as open ended as opposed to limiting. Likewise, a group ofitems linked with the conjunction “and” should not be read as requiringthat each and every one of those items be present in the grouping, butrather should be read as “and/or” unless expressly stated otherwise.Similarly, a group of items linked with the conjunction “or” should notbe read as requiring mutual exclusivity among that group, but rathershould also be read as “and/or” unless expressly stated otherwise.

Furthermore, although items, elements or components of the disclosuremay be described or claimed in the singular, the plural is contemplatedto be within the scope thereof unless limitation to the singular isexplicitly stated. The presence of broadening words and phrases such as“one or more,” “at least,” “but not limited to” or other like phrases insome instances shall not be read to mean that the narrower case isintended or required in instances where such broadening phrases may beabsent.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this disclosure belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present disclosure, the preferredmethods and materials are now described.

All publications and patents cited in this specification are cited todisclose and describe the methods and/or materials in connection withwhich the publications are cited. All such publications and patents areherein incorporated by references as if each individual publication orpatent were specifically and individually indicated to be incorporatedby reference. Such incorporation by reference is expressly limited tothe methods and/or materials described in the cited publications andpatents and does not extend to any lexicographical definitions from thecited publications and patents. Any lexicographical definition in thepublications and patents cited that is not also expressly repeated inthe instant application should not be treated as such and should not beread as defining any terms appearing in the accompanying claims Thecitation of any publication is for its disclosure prior to the filingdate and should not be construed as an admission that the presentdisclosure is not entitled to antedate such publication by virtue ofprior disclosure. Further, the dates of publication provided could bedifferent from the actual publication dates that may need to beindependently confirmed.

As will be apparent to those of skill in the art upon reading thisdisclosure, each of the individual embodiments described and illustratedherein has discrete components and features which may be readilyseparated from or combined with the features of any of the other severalembodiments without departing from the scope or spirit of the presentdisclosure. Any recited method can be carried out in the order of eventsrecited or in any other order that is logically possible.

Where a range is expressed, a further embodiment includes from the oneparticular value and/or to the other particular value. The recitation ofnumerical ranges by endpoints includes all numbers and fractionssubsumed within the respective ranges, as well as the recited endpoints.Where a range of values is provided, it is understood that eachintervening value, to the tenth of the unit of the lower limit unlessthe context clearly dictates otherwise, between the upper and lowerlimit of that range and any other stated or intervening value in thatstated range, is encompassed within the disclosure. The upper and lowerlimits of these smaller ranges may independently be included in thesmaller ranges and are also encompassed within the disclosure, subjectto any specifically excluded limit in the stated range. Where the statedrange includes one or both of the limits, ranges excluding either orboth of those included limits are also included in the disclosure. Forexample, where the stated range includes one or both of the limits,ranges excluding either or both of those included limits are alsoincluded in the disclosure, e.g. the phrase “x to y” includes the rangefrom ‘x’ to ‘y’ as well as the range greater than ‘x’ and less than ‘y’.The range can also be expressed as an upper limit, e.g. ‘about x, y, z,or less’ and should be interpreted to include the specific ranges of‘about x’, ‘about y’, and ‘about z’ as well as the ranges of ‘less thanx’, less than y′, and ‘less than z’. Likewise, the phrase ‘about x, y,z, or greater’ should be interpreted to include the specific ranges of‘about x’, ‘about y’, and ‘about z’ as well as the ranges of ‘greaterthan x’, greater than y′, and ‘greater than z’. In addition, the phrase“about ‘x’ to ‘y’”, where ‘x’ and ‘y’ are numerical values, includes“about ‘x’ to about ‘y’”.

It should be noted that ratios, concentrations, amounts, and othernumerical data can be expressed herein in a range format. It will befurther understood that the endpoints of each of the ranges aresignificant both in relation to the other endpoint, and independently ofthe other endpoint. It is also understood that there are a number ofvalues disclosed herein, and that each value is also herein disclosed as“about” that particular value in addition to the value itself. Forexample, if the value “10” is disclosed, then “about 10” is alsodisclosed. Ranges can be expressed herein as from “about” one particularvalue, and/or to “about” another particular value. Similarly, whenvalues are expressed as approximations, by use of the antecedent“about,” it will be understood that the particular value forms a furtheraspect. For example, if the value “about 10” is disclosed, then “10” isalso disclosed.

It is to be understood that such a range format is used for convenienceand brevity, and thus, should be interpreted in a flexible manner toinclude not only the numerical values explicitly recited as the limitsof the range, but also to include all the individual numerical values orsub-ranges encompassed within that range as if each numerical value andsub-range is explicitly recited. To illustrate, a numerical range of“about 0.1% to 5%” should be interpreted to include not only theexplicitly recited values of about 0.1% to about 5%, but also includeindividual values (e.g., about 1%, about 2%, about 3%, and about 4%) andthe sub-ranges (e.g., about 0.5% to about 1.1%; about 5% to about 2.4%;about 0.5% to about 3.2%, and about 0.5% to about 4.4%, and otherpossible sub-ranges) within the indicated range.

As used herein, the singular forms “a”, “an”, and “the” include bothsingular and plural referents unless the context clearly dictatesotherwise.

As used herein, “about,” “approximately,” “substantially,” and the like,when used in connection with a measurable variable such as a parameter,an amount, a temporal duration, and the like, are meant to encompassvariations of and from the specified value including those withinexperimental error (which can be determined by e.g. given data set, artaccepted standard, and/or with e.g. a given confidence interval (e.g.90%, 95%, or more confidence interval from the mean), such as variationsof +/−10% or less, +/−5% or less, +/−1% or less, and +/−0.1% or less ofand from the specified value, insofar such variations are appropriate toperform in the disclosure. As used herein, the terms “about,”“approximate,” “at or about,” and “substantially” can mean that theamount or value in question can be the exact value or a value thatprovides equivalent results or effects as recited in the claims ortaught herein. That is, it is understood that amounts, sizes,formulations, parameters, and other quantities and characteristics arenot and need not be exact, but may be approximate and/or larger orsmaller, as desired, reflecting tolerances, conversion factors, roundingoff, measurement error and the like, and other factors known to those ofskill in the art such that equivalent results or effects are obtained.In some circumstances, the value that provides equivalent results oreffects cannot be reasonably determined. In general, an amount, size,formulation, parameter or other quantity or characteristic is “about,”“approximate,” or “at or about” whether or not expressly stated to besuch. It is understood that where “about,” “approximate,” or “at orabout” is used before a quantitative value, the parameter also includesthe specific quantitative value itself, unless specifically statedotherwise.

The term “optional” or “optionally” means that the subsequent describedevent, circumstance or substituent may or may not occur, and that thedescription includes instances where the event or circumstance occursand instances where it does not.

As used herein, “polymer” refers to molecules made up of monomers repeatunits linked together. “Polymers” are understood to include, but are notlimited to, homopolymers, copolymers, such as for example, block, graft,random and alternating copolymers, terpolymers, etc. and blends andmodifications thereof. “A polymer” can be can be a three-dimensionalnetwork (e.g. the repeat units are linked together left and right, frontand back, up and down), a two-dimensional network (e.g. the repeat unitsare linked together left, right, up, and down in a sheet form), or aone-dimensional network (e.g. the repeat units are linked left and rightto form a chain). “Polymers” can be composed, natural monomers orsynthetic monomers and combinations thereof. The polymers can bebiologic (e.g. the monomers are biologically important (e.g. an aminoacid), natural, or synthetic.

As used herein, the terms “weight percent,” “wt %,” and “wt. %,” whichcan be used interchangeably, indicate the percent by weight of a givencomponent based on the total weight of a composition of which it is acomponent, unless otherwise specified. That is, unless otherwisespecified, all wt % values are based on the total weight of thecomposition. It should be understood that the sum of wt % values for allcomponents in a disclosed composition or formulation are equal to 100.Alternatively, if the wt % value is based on the total weight of asubset of components in a composition, it should be understood that thesum of wt % values the specified components in the disclosed compositionor formulation are equal to 100.

Various embodiments are described hereinafter. It should be noted thatthe specific embodiments are not intended as an exhaustive descriptionor as a limitation to the broader aspects discussed herein. One aspectdescribed in conjunction with a particular embodiment is not necessarilylimited to that embodiment and can be practiced with any otherembodiment(s). Reference throughout this specification to “oneembodiment”, “an embodiment,” “an example embodiment,” means that aparticular feature, structure or characteristic described in connectionwith the embodiment is included in at least one embodiment of thepresent disclosure. Thus, appearances of the phrases “in oneembodiment,” “in an embodiment,” or “an example embodiment” in variousplaces throughout this specification are not necessarily all referringto the same embodiment, but may. Furthermore, the particular features,structures or characteristics may be combined in any suitable manner, aswould be apparent to a person skilled in the art from this disclosure,in one or more embodiments. Furthermore, while some embodimentsdescribed herein include some but not other features included in otherembodiments, combinations of features of different embodiments are meantto be within the scope of the disclosure. For example, in the appendedclaims, any of the claimed embodiments can be used in any combination.

All patents, patent applications, published applications, andpublications, databases, websites and other published materials citedherein are hereby incorporated by reference to the same extent as thougheach individual publication, published patent document, or patentapplication was specifically and individually indicated as beingincorporated by reference.

The current disclosure provides systems and methods for measuringrolling resistance across roads. It is beneficial to compare how onetire compares to the another over range and weather conditions. Thecurrent disclosure, meanwhile, provides rolling resistance data for lifeof the tire. This enables quantification of a tire's efficiency, whichcan be reported to the driver. This system may also be used to measuredeterioration of roads over time via comparing a first new tire'sperformance at one time period to a similar make/model new tire over thesame stretch of roadway at a future point.

Field applications of existing sensing solutions to structural healthmonitoring (SHM) of civil structures are limited. This is due toeconomical and/or technical challenges in deploying existing sensingsolutions to monitor geometrically large systems. To realize the fullpotential of SHM solutions, it is imperative to develop scalablecost-effective sensing strategies. One solution as presented herein isto incorporate a network of soft elastomeric capacitors (SECs) deployedin an array form. For example, these may be deployed on the surface of atire or embedded within the tire's structure. Further, at least one SECmay be used or a group may be used in concert. FIG. 1A shows a SEC 100that may be employed with the current disclosure with a quarter 102shown for scale.

Compared with other existing sensing solutions, SEC sensors are analternative/addition to fiber optics. With both fiber optic sensors andthe SEC technology, strain data can be measured over large systems. TheSEC network offers the advantages of being 1) cost-effective; 2)operable at low frequencies; 3) mechanically robust; 4) low-powered; 5)easy to install onto surfaces; and 6) customizable in shapes and sizes.The proof-of-concept of the SEC technology has been demonstrated by theauthors with an off-the-shelf flexible capacitor. In certainembodiments, a nanoparticle mix may also be employed with the SEC.

Each SEC acts as a surface strain gage transducing local strain intochanges in capacitance. Results show that the sensor network can trackstrain history above levels of 25με using an inexpensive off-the-shelfdata acquisition system. Tests at large strains show that the sensor'ssensitivity is almost linear over strain levels of 0-20%. It is possibleto reconstruct deflection shapes for a simply supported beam subjectedto quasi-static loads, with accuracy comparable to resistive straingages.

In this disclosure, sensors measure strain in two directions. Thesensors can provide information as to how a tire deforms as it rolls andinteracts with pavement.

The relationship between stress and strain is one of the mostfundamental concepts from the study of the mechanics of materials and isof paramount importance to a stress analyst. Here, we apply a givenload, the weight of the vehicle on the tire with at least one sensor,and then measure the strain on the tire. We then use the stress-strainrelationships to compute the stresses in the tire(s). When a force isapplied to a body, the body deforms. In the general case, thisdeformation is called strain. In this application note, we will be morespecific and define the term STRAIN to mean deformation per unit lengthor fractional change in length and give it the symbol, ε. This is thestrain that we typically measure with a bonded resistance strain gage.Strain may be either tensile (positive) or compressive (negative). Whenthis is written in equation form, ε=ΔL/L, we can see that strain is aratio and, therefore, dimensionless. As described to this point, strainis fractional change in length and is directly measurable. Strain ofthis type is also often referred to as normal strain.

Another type of strain, called shearing strain, is a measure of angulardistortion. Shearing strain is also directly measurable, but not aseasily as normal strain. If we had a thick book sitting on a table topand we applied a force parallel to the covers, we could see the shearstrain by observing the edges of the pages. Shearing strain, Γ, isdefined as the angular change in radians between two line segments thatwere orthogonal in the undeformed state. Since this angle is very smallfor most materials, shearing strain is approximated by the tangent andangle.

Poisson strain, such as that measured for a bar after deformation due toa tension force, indicate that the bar not only elongates but that itsgirth contracts. This contraction is a strain in the transversedirection due to a property of the material known as Poisson's Ratio.Poisson's ratio, V, is defined as the negative ratio of the strain inthe transverse direction to the strain in the longitudinal direction. Itis interesting to note that no stress is associated with the Poissonstrain. While forces and strains are measurable quantities used by thedesigner and stress analyst, stress is the term used to compare theloading applied to a material with its ability to carry the load. Stressrefers to force per unit area on a given plane within a body. The baruniaxial tensile force, F, applied along the x-axis. If we assume theforce to be uniformly distributed over the cross-sectional area, A, the“average” stress on the plane of the section is F/A. This stress isperpendicular to the plane and is called normal stress, O′. Expressed inequation form, O′=F/A, and is denoted in units of force per unit area.Since the normal stress is in the x direction and there is no componentof force in the y direction, there is no normal stress in thatdirection. The normal stress is in the positive x direction and istensile.

Just as there are two types of strain, there is also a second type ofstress called shear stress. Where normal stress is normal to thedesignated plane, shear stress is parallel to the plane and has thesymbol T.

Here, the SECs may measure in at least two directions, such as the Y andX plane, Y and Z plane, the X and Z plane, etc., with respect to a tireand its deformation.

SECs are composed of thin flexible dielectrics, coated on both sideswith electrodes. As the SECs stretch, the electrodes get closer togetherand the change in capacitance is measured. Algorithms analyze thesechanges and create models that show the deformation of the tire. Thesesensors may be used to find the energy loss due to the deformation ofthe tire. This information may then be combined with force sensors, forinstance in the suspension system of the vehicle employing the tire(s),in order to determine most of the energy loss that contributes torolling resistance. Vehicle herein includes bicycles, automobiles,trucks, trailers, ATVs, etc., as known to those of skill in the art.

Some materials, when subjected to force, can change their resistancevalues. These are known as Force-Sensing Resistors. These materials areused to produce sensors that can measure Force. Force Sensors measurethe amount of force applied to an object. By observing the amount ofchange in the resistance values of force-sensing resistors, the appliedforce can be calculated. The general working principle of Force Sensorsis that they respond to the applied force and convert the value into ameasurable quantity. There are various types of Force Sensors availablein the market based on various sensing elements. Most of the ForceSensors are designed using Force-Sensing Resistors. These sensorsconsist of a sensing film and electrodes. Various force sensors may beapplied to the vehicle structure such as force sensors such as loadcells, pneumatic load cells, capacitive load cells, strain gauge loadcells, hydraulic load cells, force transducers, bending beams/shearbeams, tension links, load pins, compression force transducers, etc., asknown to those of skill in the art. Other examples may include foilstrain gauges (FSG) that offer a high degree of geometric variabilityand feature a high accuracy from 0.01% of FS. Even the smallest forcescan be reliably measured by such force sensors. The strain gauges areglued to the deformation body and the measuring ranges are from 0 . . .0.5 N to 0 . . . 10,000 kN. Thin-film technology is the favored variantin many, even complex, applications. Its advantage is cost efficiency.Force transducers with thin-film sensors are very cost-effective forspecial manufacture or OEM applications and also for safety-relatedapplications due to their redundant output signals. In addition, theyprovide high robustness and high long-term stability. Through thesputtering process, the measuring bridge of the force sensor isatomically connected to the measuring cell body. The measuring ranges ofthese force transducers cover from 0 . . . 1 kN to 0 . . . 10,000 kN.Hydraulic force measurement uses a combination of piston and case, withvarious seals, as a sensor unit. Due to its easy handling, itsrobustness and its operation without power supply, this form of forcemeasurement is valued by users. The measuring ranges extend from 0 . . .160 N to 0 . . . 10,000 kN. The force sensors of the current disclosuremay be placed in communication with the SECs described herein, whichdetermine energy loss due to tire deformation, and the combined sensorscan determine most of the energy loss that contributes to rollingresistance.

The working principle of a Force-sensing resistor is based on theproperty of ‘Contact Resistance’. Force-sensing resistors contain aconductive polymer film that changes its resistance in a predictablemanner when force is applied on its surface. This film consists of,sub-micrometers sized, electrically conducting and non-conductingparticles arranged in a matrix. When force is applied to the surface ofthis film, the microsized particle touches the sensor electrodes,changing the resistance of the film. The amount of change caused to theresistance values gives the measure of the amount of force applied.

Sensor Fabrication

The sensing hardware developed for strain sensing overlarge surfaces isan array of SECs acting as large-scale surface strain gages. Each SECmay be composed of a nanocom-posite mix of SEBS (Dryflex 500120) dopedwith rutile TiO₂ (Sachtleben R 320 D) serving as a dielectric for thecapacitor. The TiO₂ is selected to increase the materials permittivityand robustness with respect to mechanical tempering. This dielectric issandwiched between compliant electrodes fabricated with the same SEBSmixed with CB particles (Printex XE 2-B). FIG. 1A shows a single SEC.FIG. 1B illustrates the fabrication process of a SEC. The process isinitiated by the fabrication of a SEBS/toluene solution. Part of thissolution is used to create the nanoparticle mix, in which TiO₂ particlesare added and dispersed using an ultrasonic tip. The resulting mix isdrop-casted on a glass slide, and dried over 5 days to allow completeevaporation of the solvent. Meanwhile, the remaining SEBS/toluenesolution is used to create the compliant electrodes. Here, CB particlesare added instead of TiO₂ to create a conductive mix. Finally, the CBmix is sprayed or painted on both surfaces of the dried polymer.

FIG. 1B shows one possible method of making SECs of the currentdisclosure. The method includes dissolving SEBS in toluene 110, addingTiO₂ and dispersing same with sonication 112, drop-casting the resultingSEBS-TiO₂ solution on a glass slide 114, adding CB and dispersing sameusing sonication 116, and painting a CB solution on the SEBS-TiO₂polymer 118.

Sensing Principle

The capacitance C of a SEC is written:

$\begin{matrix}{C = {e_{0}e_{r}\frac{A}{h}}} & (1)\end{matrix}$

the dielectric. Given a unidirectional strain in the length l of thesensor (Δw=0, due to the epoxy), a small change in C can be obtainedfrom Eq. (1) by expressing the differential ΔC as:

$\begin{matrix}{{\Delta \; C} = {\left( {\frac{\Delta \; l}{l} - \frac{\Delta \; h}{h}} \right)C}} & (2)\end{matrix}$

The Poisson ratio of pure SEBS materials has been re-ported to be 0.49.The elastomer can be assumed to be incompressible, where the nominalvolume V=w·l·h will be preserved after the SEC geometric deformations Δtand Δh:

$\begin{matrix}{{{w \cdot l \cdot h} = {\left( {l + {\Delta \; l}} \right)\left( {h + {\Delta \; h}} \right)w}}{\frac{\Delta \; l}{l} \approx {- \frac{\Delta \; h}{h}}}} & (3)\end{matrix}$

In now follows from Eqs. (1) to (3) that:

$\begin{matrix}{{\frac{\Delta \; C}{\Delta \; l} = {2\; \frac{e_{0}ɛ_{r}w}{h}\mspace{14mu} {or}}}{\frac{\Delta \; C}{ɛ_{s}} = {2C}}} & (4)\end{matrix}$

Where ε_(s) is the sensor strain. Eq. (4) represents the sensitivity ofthe sensor. This sensitivity can be increased by decreasing the SECthickness, increasing the width, or in-creasing the dielectricpermittivity, which is attained by altering the nanocomposite mix. It istherefore possible to customize the sensitivity for a given geometry.For the SEC shown in FIG. 1A (C≈595 pf, w=l=70 mm, h=0.3 mm), theresulting sensitivity is:

$\begin{matrix}{{\frac{\Delta \; C}{\Delta \; l} = {17.0\mspace{14mu} {pF}\text{/}{mm}\mspace{14mu} {or}}}{\frac{\Delta \; C}{ɛ_{s}} = {1190\mspace{14mu} {pF}\text{/}ɛ_{m}}}} & (5)\end{matrix}$

Note that the sensitivity of each SEC may vary by ±20% due to the manualfabrication process. The sensing principle for the sensor consists ofdirectly measuring the relative changes in capacitance of a SEC overtime. FIG. 1C illustrates the measurement principle. The sensor isadhered onto the monitored surface using an epoxy. A strain on themonitored surface provokes a change in the sensor geometry Δl, which ismeasured by the data acquisition system (DAQ) as a change in thecapacitance ΔC, or the relative change ΔC/C, where C is the nominalcapacitance. FIG. 1C shows a measurement principle 120 of the currentdisclosure.

SEC Signal-Strain Model

Several models have been studied to describe the stress-strainrelationship for thermoplastic elastomers, which is dominated by anonlinear rate-dependent response. This nonlinear response is furthercomplicated by additional nonlinearities from the hysteresis andMullins' effect. A typical constitutive model used to represent themechanical behavior is a three-parameters rheological model, in which anelastic spring and a visco-plastic dashpot in series are installed inparallel with a hyper-elastic rubbery spring. The three-parameter modelhas been used in civil engineering, for system identification of rubberbearings used for base-isolation. In the proposed application, we assumethat the materials on which the polymer is bonded significantly stifferthan the SEC. For a two-dimensional bending beam subjected to lowfrequency excitations, one can write:

$\begin{matrix}{ɛ_{s} = {ɛ_{m} = {{- c}\; \frac{\delta^{2}y}{\delta \; x^{2}}}}} & (6)\end{matrix}$

Where ε_(m) is the strain of the monitored beam surface, c is thedistance from the surface to the centroid of the beam, y is thedeflection (downwards in FIG. 1D), and x is the longitudinal Cartesiancoordinate (leftwards in FIG. 1D). FIG. 1D shows a laboratory setup forfour SECs: at (a): general setup with four SECs installed on the bottomof the beam 140; and at (b) setup schematic—from side 142; and (c) setupschematic 144—from under the beam. Using Eqs. (4) and (6), one obtains agage factor independent of the nanoparticle mix:

$\begin{matrix}{\frac{\frac{\Delta \; C}{C}}{ɛ_{m\;}} = 2} & (7)\end{matrix}$

Shape Reconstruction

The problem of real-time reconstruction of deflection shapes fromposition and curvature measurements from sensor networks has been widelystudied, with applications to condition assessment, SHM, and shapecontrol. Here, we select the polynomial interpolation method forreconstructing the deflection shapes from a network of curvature data, atechnique also used to smoothen data. The algorithm consists of fittingthe curvature data using a polynomial function. In the case of atwo-dimensional beam equipped with four sensors, the fitting function istaken as a third degree polynomial to avoid possible over-fitting.

{circumflex over (ε)}_(m,j) =a ₀ +a ₁ x _(j) +a ₂ x _(j) ² +a ₃ x _(j)³  (8)

where the hat denotes an estimation for the j^(th) sensor. Minimizingthe error J for n sensors:

$\begin{matrix}{J = {\sum\limits_{j}^{n}\left( {ɛ_{m,j} - {\hat{ɛ}}_{m,j}} \right)^{2}}} & (9)\end{matrix}$

leads to the expression:

A=(X ^(T) X)⁻¹ X ^(T)Ξ_(m)  (10)

with:

$\begin{matrix}{{A = \begin{bmatrix}a_{0} \\a_{1} \\a_{2} \\a_{3}\end{bmatrix}}{\Xi_{m} = \begin{bmatrix}ɛ_{m,1} \\ɛ_{m,2} \\\ldots \\ɛ_{m,n}\end{bmatrix}}{X = \begin{bmatrix}1 & x_{1} & x_{1}^{2} & x_{1}^{3} \\1 & x_{2} & x_{2}^{2} & x_{2}^{3} \\\vdots & \vdots & \vdots & \vdots \\1 & x_{n} & x_{n}^{2} & x_{n}^{3}\end{bmatrix}}} & (11)\end{matrix}$

Once the parameters A are determined, the deflection shape is obtainedby integrating the curvature twice:

$\begin{matrix}\begin{matrix}{{y(x)} = {\int_{0}^{L}{\int_{0}^{L}{\frac{\delta^{2}y}{\delta \; x^{2}}{dx}^{2}}}}} \\{= {\int_{0}^{L}{\int_{0}^{L}{{- \frac{1}{c}}\left( {a_{0} + {a_{1}x_{j}} + {a_{2}x_{j}^{2}} + {a_{3}x_{j}^{3}}} \right){dx}^{2}}}}} \\{= {{{- \frac{1}{c}}\left( {{a_{0}\frac{x^{2}}{2}} + {a_{1}\frac{x^{3}}{6}} + {a_{2}\frac{x^{4}}{12}} + {a_{3}\frac{x^{5}}{20}}} \right)} + {b_{1}x} + b_{2}}}\end{matrix} & (12)\end{matrix}$

where L is the length of the beam. Enforcing the boundary conditionsy(0)=y(L)=0 for a simply-supported beam, one obtains:

$\begin{matrix}{{b_{1} = {\frac{1}{C}\left( {{a_{0}\frac{L}{2}} + {a_{1}\frac{L^{2}}{6}} + {a_{2}\frac{L^{3}}{12}} + {a_{3}\frac{L^{4}}{20}}} \right)}}{b_{2} = 0}} & (13)\end{matrix}$

Experimental Setup

In this section, the proposed sensor network is validated using 1) asingle SEC; and 2) four SECs organized in a network, both measuringsurface strain of a bending beam. An additional test is conducted on afree-standing sensor to study its behavior under large levels of strain(0-20%). We use the same SEC sensor size as shown in FIG. 1A tocharacterize the performance of a full-scale sensor. Bending beam testsare conducted in a three-point load setup on a simply supported aluminumbeam of support-to-support dimensions 406.4×101.6×6.35 mm³ (16×4×0.25in³). A typical experimental setup is shown in FIG. 1D. SECs and RSGsare installed following a similar procedure. The monitored surface issanded, painted with a primer, and a thin layer of an off-the-shelfepoxy (JB Kwik) is applied on which the sensors are adhered.

In the single SEC bending tests, the SEC and strain gage are locatedunder the beam at x=0.50 L. For the four SECs tests, the SECs and straingages are located under the beam at x={0.20,0.40,0.60,0.80}L, as shownin FIG. 1D at (b) and (c). The load is applied using a hand operatedhydraulic test system (Enerpac) for the static tests, and aservo-hydraulic fatigue testing machine (MTS) for quasi-static tests.All tests are repeated three times. In the free-standing tests, thesensor is pre-stretched at approximately 1.5% strain and subjected to auniaxial tensile strain using an Instron universal testing machine(model 5569).

Data from the SECs are acquired using an inexpensive off-the-shelf dataacquisition system (ACAM PCap01) sampled at 95.4 Hz for the single SECsetup (including the free-standing setup), and 48.0 Hz for the four SECssetup. The SEC readings are compared against RSG with resolution of 1με(Vishay Micro-Measurements, CEA-06-500UW-120). Strain gage data areacquired using a Hewlett-Packard 3852 data acquisition system, and datasampled at 1.7 Hz when using the hand hydraulic, and 55 Hz when usingthe MTS. Data are filtered using a low-pass filter, and zeroed using theaverage capacitance while the beam is unloaded.

Validation of the SEC

A single SEC is first validated using a step load. FIG. 1E is a plot ofthe results, in which the capacitance signal has been transformed intostrain using Eq. (7). The SEC signal raises above noise beyond 25με, butfor strain levels above 55με, there is a constant difference ofapproximately 8 pc. FIG. 1F shows the results from a typicalquasi-static load test. The excitation history consists of adisplacement-based triangular wave loads with increasing frequenciesfrom 0.0167 to 0.40. Results show that the SEC is capable of tracking aquasi-static strain history within a given level of resolution. FIG. 1Gis a plot of the SEC readings in function of the strain measured by theRSG, validating the linearity of the sensor. Its measured sensitivity isin agreement with Eq. (5). Given that the dielectric permittivity doesnot change significantly in the low frequency range (<100 Hz), a largeportion of the measurement errors in both FIGS. FIGS. 1E and 1F can beattributed to the electronics. Firstly, there is parasitic capacitancein the cables connecting to the sensors, which cause variations in themeasured capacitance. Because SECs require very small power, this noisecan be minimized by digitizing the signal at the source, enabling longdistance transmissions, either over a wired or wire-less link, withessentially no signal degradation. Secondly, the DAQ itself may not havethe sufficient resolution for measuring small changes in capacitance.For instance, using Eq. (5), the measurement of 1με over the SECcorresponds to measuring a change of 0.00140 pF.

Thirdly, there is a small linear drift in the signal. This drift can beseen in both FIGS. 1E and 1F, where the SEC signal does not return tothe zero strain line. While this drift could be filtered out, futuredevelopments in dedicated DAQ systems for SEC measurements may minimizethis noise. Other sources of error may come from imperfections in thesensor fabrication and geometry, and/or a slight angle in theapplication of the sensor, which would change the geo-metricrelationship described in Eq. (2). A net advantage of the SEC is itshigh elasticity com-pared to conventional strain transducers, enablingmeasurements of large strain levels. To study the behavior of the SEC atlarge strains, the sensor is subjected to a triangular strain rampingfrom 0 to 20% in approximately 2% increments. FIG. 1H shows a plot ofthe measured capacitance versus applied strain after pre-stretch, alongwith the applied strain history. Results show that the sensor exhibits aslight nonlinearity over the range 0-20%. Note that, in a free-standingsetup, the sensitivity cannot be obtained using Eq. (5), because εy doesnot equal 0. Also, the differential form of Eq. (1) given by Eq. (2)does not apply for large strain, which explains the loss in linearitycompared to FIG. 1G. Nevertheless, it is possible to model the nonlinearsensitivity of the sensor for large strain measurements.

Shape Detection Using Sensor Network.

This subsection demonstrates a SHM application using a network of SECs.Strain measurements from four SECs are used to reconstruct thedeflection shapes using the representation from Eq. (12). Note that thedouble integration of strain data to reconstruct the deflection shapemay cause an accumulation of errors. This effect is minimized by theutilization of the polynomial fit that inherently filters the straindata, and by the enforcement of the boundary conditions (y(0)=y(L)=0).In implementations, it would be also possible to further reduce theerror, for instance, by averaging the resulting shapes within smallperiods of time, depending on the sampling rate. FIG. 1I shows thestrain time history of the four SECs subjected to a static load. Thecomparison of results between FIG. 1I at (a) and (b) show that theresults from the SECs agree with the RSGs at low levels of strain(<100με), but the discrepancy increases with the level of strain,reaching up to 100 pc. Note that the small difference between symmetricstrain gages (RSG₁ versus RSG₄ and RSG₂ versus RSG₃) can be explained bya slight off-centered installation of sensors and/or application of theload.

Using the surface strain data for FIG. 1I, the deflection shapes areestimated and shown in FIG. 1J for a typical result (at time t=25 s).The shape obtained from the SECs is compared against the shape obtainedfrom the RSGs using the same procedure as described herein. Results arecompared against the analytical solution using Euler-Bernoulli beamtheory:

$\begin{matrix}{{y(x)} = {{{- \frac{Px}{48{EI}}}\left( {{3L^{2}} - {4x^{2}}} \right)\mspace{14mu} {for}\mspace{14mu} 0} \leq x \leq \frac{L}{2}}} & (14)\end{matrix}$

where y(x) is symmetry about L/2, P=120 N is the applied load at timet=25 s, and E and I are the Young's modulus and moment of inertia of thebeam, respectively. FIG. 1J at (a) compares the non-normalized results.The underestimation of strain for the SECs clearly results in anunderestimation of the magnitude of the shape. In applications to SHM,the normalized deflection shape might be more informative to detectdamages or changes in the structural behaviors. FIG. 1J at (b) shows theshapes normalized to a maximum deflection of −1. Results from the SECscompare well against RSGs and the analytical solution. The averageroot-mean-square (RMS) error of the normalized deflection shapes for theduration of the load P=118 N (for 20.6 s≤t≤28.8 s) is 0.208 mm/mm forthe SECs and 0.376 mm/mm for the RSGs, showing a comparable, yetimproved, normalized shape. Taken over the entire length of the test,the average RMS errors augment to 1.32 mm/mm and 3.50 mm/mm for the SECsand RSGs, respectively. This increase is due to the larger errors at theunloaded conditions, during which the polynomial reconstruction givesinaccurate results. Lastly, we subject the specimen to the triangularload(displacement-based) with increasing rate described herein. Thestrain time histories for the SECs and RSGs, and the actuatordisplacement history are shown in FIG. 1K.

Results show that the SECs are capable of tracking the strain history,but that the SECs increasingly underestimate strain with increasingstrain magnitude, except for SEC₃ which is overestimating strain.Another feature is that SEC₂ is showing an important difference withrespect to SEC₃ in the measurements, a difference minimized between RSG₂and RSG₃. Note that this difference should theoretically be zero if thesensors are placed symmetrically. This difference was not observed inthe triangular load test, see FIG. 1I. As discussed above, a smalloffset in the installation can explain the difference between RSG₂ andRSG₃. FIG. 1L compares the root mean square (RMS) error of thenormalized deflection shapes with respect to the analytical solution.The SEC network obtains a more accurate shape than the RSG networkbeyond an initial level of loading. Here as well, when the beam isunloaded, the noise in the sensors signals results in inaccuratedeflection shapes. The significant difference in performance betweenboth sensors can be attributed to the SECs averaging strain over a largearea, while the RSGs measure a localized strain. SECs are less sensitiveto placement errors.

We have presented a sensor network developed for strain sensing overlarge surfaces. The network consists of SECs arranged in an array form,transducing strain into changes in capacitance. These elastomericsensors are fabricated in-laboratory using solutions of SEBS+TiO₂ forthe dielectric and SEBS+CB for the compliant electrodes. Results fromthe experimental validation demonstrated that the sensor compares wellagainst off-the-shelf resistive strain gages. Given the relative size ofa single SEC com pares with a RSG, it follows that the sensor can beused as a surface strain gage capable of covering large areas. It wasalso shown that the sensor can measure large strains, in the levels of0-20%. The installation procedure used for the laboratory experimentsconsisted of a hand-installation using an off-the-shelf epoxy. Thisdemonstrates the easy applicability of the sensing solution. Further,sensors may be integrated into structures such as tires, either embeddedinternally or applied externally to achieve the results describedherein.

Results also show the sensor has a tendency to underestimate strain. Theunderestimation of strain can be due to parasitic capacitance from thewires, complexity in measuring low changes in capacitance usingoff-the-shelf DAQ, drift in the signal, impurities in the sensorfabrication, and/or inconsistencies during the manual installation. Weenvision the development of dedicated data acquisition systems formeasuring differential capacitance, which would increase the resolutionof the sensor at levels comparable to conventional strain gages. Thisunderestimation of strain limits the capability of extracting accuratephysics-based features associated with non-normalized displacementvalues.

The SEC sensor network has been demonstrated in a four SECs setup todetect deflection shapes of a simply supported beam. The deflectionshapes have been reconstructed using a simple polynomial algorithm.Results have shown that the SECs were underestimating the real shape,consistent with results discussed above, but were estimating thenormalized deflection shapes accurately. Comparisons with RSGs showedthat the SECs were estimating the normalized shapes with less error.This good performance can be explained partly by the capacity of theSECs to average strain over a large area, unlike RSGs that measurelocalized strain. This particularity represents a strong advantage ofSECs over RSGs.

The proposed sensor network is a promising tool for conducting SHM atthe mesoscale. In a network setup, the network could be used to collecttwo-dimension strain data, from which physics-based features can beextracted, including over-stresses, torsion, utilization history, etc.These features can subsequently be utilized as input to forecast modelsto conduct structural diagnostic and prognostic. Possible applicationsother than extraction of deflection shapes include crack detection andlocalization on concrete structures, detection of permanent deformationson steel members, and weigh-in-motion sensing.

Herein, the SECs of the present disclosure are composed of thin flexibledielectrics, coated on both sides with electrodes. As the SECs stretch,the electrodes get closer together and the change in capacitance ismeasured. Algorithms analyze these changes and create models that showthe deformation of the tire.

FIG. 2 shows a cross section 200 of an automobile tire. Sensors of thecurrent disclosure may be inserted internally into a tire, such as shownvia 202 between fabrication layers or on the side wall 204 or runningsurface 206 of the tire.

FIG. 3 shows an illustration of tire deformation 300. The behavior ofelastomeric materials is controlled by the inherent nonlinearviscoelasticity. The nonlinear behavior makes the material strain-ratedependent and lose energy during cyclic loading (hysteresis). Thesebehaviors are important for many applications, for example whendetermining the footprint of a tire. In one embodiment, on may use theBergstrom-Boyce (BB) model in PolyUMod® to determine the footprint of aninflated tire that is vertically loaded. The BB model can be used todetermine the change in contact area, and the stress and straindistributions as a function of time. The PolyUMod library, originallydeveloped by Veryst, is now available on PolymerFEM.com. Tiredeformation 302 may be used to determine how a tire interacts with aroad surface in order to determine and calculate rolling resistance.

The system may also include/work with an integrated roadway, such as athe modular system developed by Integrated Roadways. The integratedroadway may be made from a precast concrete section with dowels to forma Jointed Reinforced Concrete Pavement (JRCP). JRCP uses contractionjoints and reinforcing steel to control cracking. Transverse jointspacing is longer than that for JPCP and typically ranges from about 7.6m (25 ft.) to 15.2 m (50 ft.). Temperature and moisture stresses areexpected to cause cracking between joints, hence, reinforcing steel or asteel mesh is used to hold these cracks tightly together. Dowel bars aretypically used at transverse joints to assist in load transfer while thereinforcing steel/wire mesh assists in load transfer across cracks.

FIG. 4 shows an example of integrated roadway section 400. The sectionmay include access ports 402. Access ports 402 may be a Combined AccessPort (CAP) that may be used to lift and position the section ofintegrated roadway slab into place. Once positioned, void with interiorconnector accommodates a sensor cylinder 404, which may containprocessors, antennae and other technology installed within sensorcylinder 404, while remaining easily accessible for replacement orupgrade. Integrated roadway section 400 may also include a digitizerlayer/vehicle detection loop 406, wherein a fiber optic strain mesh 408is laminated to the slab's reinforcement. This is similar to a touchscreen element and can identify tire positions rather than fingerpositions. Integrated roadway section 400 may also include at least onerouter 410 connected to neighbor sections of integrated roadway section400 via wiring, fiber optics, Wi-Fi, etc., shown as 411, and may sendinformation to a data center alongside the highway, not shown,containing integrated roadway section 400. Integrated roadway section400 may also include a dowel and conduit system 412. Dowel and conduitsystem 412 may comprise a series of dowels 414 extending into adjacentconduits, not shown, then filled with grout, or another suitable mixtureas known to those of skill in the art, to form a solid connection. Muchlike the touchscreen on a smartphone or tablet, sensors in integratedroadway section 400 can “feel” the positions, weights and velocity ofevery vehicle on the road, providing superior navigation and telemetry.This may even be used for Level 4 autonomous vehicles and capturingvaluable traffic and usage data. Further, integrated roadway section 400is completely upgradable, making it easy to add new features. Further,each slab is easily removable for repair or to access underlyingutilities for service. Integrated roadway section 400 may alsoincorporate axis accelerometers 416 that measures vibrations in additionto sensing fiber optic cable 408 that measures strain in concrete.Further sensors may include a magnetometer to measure axle width todetermine car type, a gyroscope to determine the actual position of theconcrete slab. This data may run through power over an Ethernetconnection to control centers. As FIG. 5 shows, integrated roadwaysection 400 may be further upgraded to provide features like snow andice 500 melt functionality 502 and wireless charging 504 for electricvehicles.

FIG. 6 shows an example of a 3D printed biodegradable tire 600 withairless support structure 602, which is shown as a “honeycomb” or opencell/vessel formation. While shown as such, other variations are hereinconsidered disclosed, such as open cell/closed cell hybrids, “tunnels”,etc. Tire 600 may be formed via 3-D printing with printed tread 604 onthe tire rather than formed via attachment of a separate layer havingpreformed tread. Various polymers, including but not limited tobiodegradable polymers, may be used to form tire 600. Openings 606lessen weight as well and may be shaped to improve aerodynamics, airflow, lessens friction etc., with shapes such as wedge, “clover leaf,”spirals, etc., with the shapes being uniform with respect to an outerfacing shape 608 and maintaining this shape throughout depth 610 of tire600 or the shape may change as the opening moves/penetrates from outerfacing shape 608 into depth 610 of tire 600. 3-D printing would do awaywith the current practice of forming tires from layers affixed toanother via adhesives, vulcanization, melt-formed, etc., and would allowfor great product control as the tire is “deposited” and formed in asingle step.

Tire 600 may be used with the SECs and integrated roadway technology todetermine the conditions for the tread depending on the route traveled.Bridgestone airless tire technology features a unique spoke structuredesigned to support the weight of a vehicle, effectively eliminating theneed to periodically refill the tires with air. Tire 600 may be an airfree concept non-pneumatic tire featuring improved load-bearingcapabilities, environmental design and driving performance. Currently,most airless tires on the market are made from solid rubber or plastic.Golf carts, trailers and lawnmowers are a few examples of these tiresbeing used in commercial applications. Airless tires have numerousbenefits, including no flat tires, never having to worry about tiresleaking because as non-pneumatic tires have no air to leak, no need tocarry a spare tire, freeing up trunk space, lessening vehicle weightthereby increasing fuel economy. Further, loss of time due to tirefailure would also be significantly reduced.

As about 90% of energy loss from tire rolling resistance comes fromrepeated changes in the shape of the tries as they roll. By simplifyingthe structure of the tire, this will minimize the energy loss in “airfree tires.” As a result, these tires have the same level of low rollingresistance as fuel efficient tires, such as the Ecopia tires fromBRIDGESTONE, contributing to reductions in CO₂ emissions.

The vast majority of airless designs follow a similar theme. An outerring is fitted with a rubber tread, which connects to the hub with aseries of polymer spokes. The weight of the vehicle hangs from the topof the ring, placing the spokes in tension. BRIDGESTONE and SUMITOMOhave both displayed prototype designs. MICHELIN recently announced itsnew Uptis design, which has a chevron shape to the spokes. One of themain benefits is lateral stability. In standard radial tires, it's notpossible to improve lateral stiffness without affecting other propertiesof the tire. Stiffening the tire in this way can lead to the tireoffering a harsh ride, particularly over bumpy surfaces. However, due tothe construction of the airless designs, the tire can be made to beforgiving in the vertical axis, while being stiff from side-to-side.This has the benefit of making handling far more sharp, which is ofparticular interest for sporting and high-performance applications.

The contact patch of an airless tire is another point of interest.Unlike air-filled tires, which by necessity bulge out at the sides withair pressure, the contact patch of an airless tire can be far moreconsistent and flat. By having no air, it no longer rests on thedriver's shoulders to ensure their tires are sitting at the correctpressure to maintain the proper contact patch.

Another boon of the technology is wear. Despite tire pressure monitorsnow being widespread, and manufacturers trying to educate drivers aboutproper tire rotation practices, very few consumers take good care oftheir tires. Running under or overinflated can prematurely wear a set oftires, but with airless design, this isn't an issue. Additionally,manufacturers claim that it should be possible to easily and safelyreplace the tread on such designs, with little to no degradation inperformance. This would have huge sustainability ramifications; currentestimates are that 1.5 billion tires are discarded each year. Anyimprovements in the recyclability of tire components could have a majorimpact.

Having an airless design brings the possibility of perforating the tireto create channels for water to flow away. By no longer requiring thewater to be pushed out from under the tire. Developments in this areacould greatly reduce the chance of aquaplaning when driving throughstanding water. Since aquaplaning can lead to total loss of control of avehicle, any improvements in this space have the potential to save moneyand lives.

FIG. 7 shows one embodiment of a potential airless tire 700 formed froman outer tire tread 702, a flexible spoke array 704, which may be formedin a honeycomb, “star” array, lateral array, etc., a deformable wheel706, and a sheer band 708. A solid inner hub mounts to the axle.

For example, airless tire 700 may include a polyurethane, or otherpolymer, spoke array 704 in a pattern of wedges or other shapes. Shearband 708 is stretched across the spokes, forming the outer edge of thetire (the part that comes in contact with the road). The tension ofshear band 708 on the spokes and the strength of the spokes themselvesreplace the air pressure of a traditional tire. Tread 702 is thenattached to shear band 708. The spokes absorb road impacts the same wayair pressure does in pneumatic tires. The tread and shear bands deformtemporarily as the spokes bend, then quickly spring back into shape.These wheels can be made with different spoke tensions, allowing fordifferent handling characteristics. More pliant spokes result in a morecomfortable ride with improved handling. The lateral stiffness of tire700 is also adjustable.

Various modifications and variations of the described methods,pharmaceutical compositions, and kits of the disclosure will be apparentto those skilled in the art without departing from the scope and spiritof the disclosure. Although the disclosure has been described inconnection with specific embodiments, it will be understood that it iscapable of further modifications and that the disclosure as claimedshould not be unduly limited to such specific embodiments. Indeed,various modifications of the described modes for carrying out thedisclosure that are obvious to those skilled in the art are intended tobe within the scope of the disclosure. This application is intended tocover any variations, uses, or adaptations of the disclosure following,in general, the principles of the disclosure and including suchdepartures from the present disclosure come within known customarypractice within the art to which the disclosure pertains and may beapplied to the essential features herein before set forth.

What is claimed is:
 1. A system for monitoring rolling resistance acrossa road comprising: a vehicle with at least one tire; the at least onetire having at least one tire sensor incorporated into a structure ofthe tire; and wherein movement of the at least one tire across a roadsurface impacts the at least one tire sensor and provides rollingresistance data for the at least one tire.
 2. The system of claim 1,wherein the at least one tire sensor is a soft elastomeric capacitor. 3.The system of claim 1, wherein the at least one tire sensor is on anexterior surface of the tire.
 4. The system of claim 1, wherein the atleast one tire sensor is placed within an interior structure of the atleast one tire.
 5. The system of claim 1, wherein the system measuresenergy loss that contributes to rolling resistance of the at least onetire.
 6. The system of claim 1, wherein the system includes anintegrated roadway section.
 7. The system of claim 6, wherein theintegrated roadway system includes a precast concreate section with atleast one sensor embedded within the precast concrete.
 8. The system ofclaim 1, wherein the at least one tire sensor measures strain in atleast two directions.
 9. The system of claim 1, wherein deformation ofthe at least one tire is measured to determine rolling resistance. 10.The system of claim 1, wherein the at least one tire has an airlesssupport structure.
 11. The system of claim 10, wherein the at least onetire is a 3-D printed tire.
 12. The system of claim 10, wherein the atleast one tire is formed from a biodegradable polymer.
 13. The system ofclaim 11, wherein tread is printed on an outer surface of the 3-Dprinted tire.
 14. A method for calculating rolling resistance across aroad comprising: forming at least one tire having at least one tiresensor incorporated into a structure of the tire; placing the tire on avehicle; placing at least one force sensor within a suspension of thevehicle in communication with the at least one tire sensor; and whereinmovement of the at least one tire across a road surface impacts that atleast one tire sensor and provides rolling resistance data for the atleast one tire.
 15. The method of claim 14, further comprising whereinthe at least one tire sensor is a soft elastomeric capacitor.
 16. Themethod of claim 14, wherein the at least one tire sensor is placed on anexterior surface of the tire.
 17. The method of claim 14, wherein the atleast one tire sensor is placed within an interior structure of the atleast one tire.
 18. The method of claim 14, further comprising measuringenergy loss that contributes to rolling resistance of the at least onetire.
 19. The method of claim 14, further comprising driving the vehicleover an integrated roadway section.
 20. The method of claim 14, whereinthe at least one tire is formed with an airless support structure.